This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.
Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds.
Sample Chapter(s)
Preface
Chapter 1: Introduction
Contents:
Readership: Professionals, researchers, academics, and graduate students in databases, artificial intelligence, pattern recognition and neural networks.